Cyclistic Data Analytics
Project
Engage casual users to sign in members users
Yolanda Aguilar Sanchez
12/07/2023
Cyclistics Co.
Chicago bike sharing
Company.
Contents:
•Data set.
•Summary.
•Conclusions.
•Recommendations.
•References.
2
Data set
Resources and data set treatment and problems.
•All data used in the current análisis have been proporcionated by the
Marketing department records and treated under company policies.
•The historical range recods: from June 2022 to May 2023.
•Total ride trips used 582677.
•Total ride trips cleaned 2054.
•Total rows with missing values on station names or id 1334349.
•The data set with missing values rows have been provided for further
analysis due the huge amount of missing values.
→ Note: Link to all reports Project, included data sets. Click
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Summary
•Analyzed data of Cyclistics marketing department from June 2022 to May 2023 to
identify how the different type of users use Cyclistic bikes and identify differences and
trends.
•Number of rides:
• The number of ride of members are considerably higher during the whole week
with the peak on Wednesday having the lowest rates during the weekend.
• The casual users trends are the opposite starting at lowest rate on Monday and
increasing gradually till Saturday where there is the peak of the week being
Saturday and Sunday the higher rates of the week
• In Total the member users do more rides than casual.
• Average duration trips:
• Casual users have considerably higher rates versus the members users being the
weekend uses the longer trips of the week for both, Casual users use to double the
duration of the trips versus the members.
• Monthly trends:
• Member users have higher rates on rides from May to October.
• While Casual users from June to September.
• End hour trends:
•There are no remarkable differences in how both users types uses the service, but
both users have the lowest rates in the morning.
For the marketing strategies to convert casual to member users we must pay
attention to seasonality, the weekend use.
Surprise: Maximum ride length show as that sometimes the bikes are not
returned at end station until days later..
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How casual riders and annual members use Cyclistic bikes differently?
Ride length
Ride Length
•Min. 1st Qu. Median Mean 3rd Qu. Max.
1 335 591 1123 1057 2483235
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How casual riders and annual members use Cyclistic bikes differently?
Ride length
Ride Length
•Min. 1st Qu. Median Mean 3rd Qu. Max.
1 335 591 1123 1057 2483235
6
Visualize the
differences
Between Casual Users and Member Users
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8
By Users types.
Number of Ride Average Duration
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By Users types.
Number of Ride Average Duration
Members rides
10
By Users types.
Number of Ride Average Duration
Casual Users
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By Users types.
Number of rides Ride duration
12
By Users types.
Number of rides Ride duration
Members rides
Casual Users
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By Users types.
Members rides
Casual Users
Recomendations
•Main differences between member and casual users
are number of rides and uses in weekend.
•To engage the Casual users to sign in Member.
• Offer annual member ship for weekend trips.
• Due the casual trips of casual users are longer ,
could mean that there are from the extra radius, I
recommend analyze why there are so missing data
on stations names and do a further analysis with the
metrics of position, stations names and get the data
set of population of Chicago .
• This extension of the analysis will hep us to find.
• most traffic of users in stations and we could check
if there any business that could do some
collaboration with us and that could increase the
casual users.
• I recommend as well a study of the longest trips.
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References
• This analisis have been created with Rstudio,
powerpoint and excel files.
• All the images and the logo, have been created with AI.
• Logo : https://looka.com/
• Images : https: https://starryai.com/
• Report Project in Rstudio: Cyclistic Analysis Project
• Report cleaning data and analysis (Markdown):
Cyclistic_Analisys_Project.pdf
• Files data Cleaned not included on analysis:
Removed data from Cyclists files (csv format)
• Files data with missing Values for further analysis:
All rides with missing values (station information)
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